IDEAS home Printed from https://ideas.repec.org/h/spr/dymchp/978-3-319-12805-4_3.html
   My bibliography  Save this book chapter

Parametric Models in Spatial Econometrics: A Survey

In: Complexity and Geographical Economics

Author

Listed:
  • Diana A. Mendes

    (ISCTE-IUL and BRU-IUL)

  • Vivaldo M. Mendes

    (ISCTE-IUL and BRU-IUL)

Abstract

The main purpose of this chapter is to review the parametric spatial econometric models that can be applied to regional economics. Spatial econometric methods are based on regression analysis applied to cases where spatial interactions and spatial structures are fundamental characteristics of the process under discussion. The review presented here outlines the basic terminology, the spatial data dependence, the specification of spatial effects, and some basic spatial regression models, i.e., the spatial autoregressive (SAR) model (or spatial lag model), the spatial error model (SEM), the spatial Durbin model (SDM) and the general spatial models—SAC and SARMA. The maximum likelihood estimation for SAR and SEM models it is also presented with some detail.In the context of the European Union, we should emphasize several empirical works in the particular areas of urban economics, economic growth and productivity, and studies dealing with agglomeration and externalities (spillovers). We provide a brief survey of some of the results obtained in these particular areas.

Suggested Citation

  • Diana A. Mendes & Vivaldo M. Mendes, 2015. "Parametric Models in Spatial Econometrics: A Survey," Dynamic Modeling and Econometrics in Economics and Finance, in: Pasquale Commendatore & Saime Kayam & Ingrid Kubin (ed.), Complexity and Geographical Economics, edition 127, pages 51-71, Springer.
    • Handle: RePEc:spr:dymchp:978-3-319-12805-4_3
    DOI: 10.1007/978-3-319-12805-4_3
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Federico Cingano & Marco Tonello, 2020. "Law Enforcement, Social Control and Organized Crime: Evidence from Local Government Dismissals in Italy," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 6(2), pages 221-254, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:dymchp:978-3-319-12805-4_3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.